UM achieves new breakthrough in biochip research

The University of Macau (UM) has
achieved a breakthrough in the research of biochips. The Computational Biology
and Bioinformatics Lab (CBBio), under UM’s Faculty of Science and Technology,
and the State-Key Laboratory of Analog and Mixed-Signal VLSI, have successfully
developed a computational intelligence-based software programme to address the
challenges of conformational sampling in 3D protein-surface structure
prediction, which helps to produce biochips with the ability to locate the
optimal protein configuration in the most promising low-energy region. The work
was recently published by Oxford University Press’s journal Bioinformatics, the most authoritative
publication in the field of bioinformatics and computational biology.

In order to predict the optimal protein
configuration computationally, the research team translated the problem into an
optimisation task, to search intelligently among all possible orientations and
positions of protein with respect to the surface, for the most promising
low-energy region where the optimal is. Inspired by nature, the ‘intelligent’
part of the project is based on the social behaviour model of bird flocking
when searching for food. Birds in a flock would memorise places where the most
food has been found, and communicate with one another to update the best food
source. Based on this knowledge, the birds iteratively adjust their flying
direction towards previously successful regions until no better food source is
found.

By combining the search model with a
newly devised forcefield-based energy function describing the protein-surface
interactions and fine-tuned parameters, the research team has created an
efficient computer algorithm to address the protein-surface structure
prediction problem, ProtPOS. The programme (http://cbbio.cis.umac.mo/software/protpos/)
can work seamlessly with most popular molecular simulation software, so
prediction results can be used right away in further computational studies for
biochip design.

The research project was conducted by UM PhD student
Ngai Choi Fong, jointly supervised by Dr Shirley Siu Weng In and Prof Elvis Mak
Pui In, and funded by UM.